Advances in Non-Linear Modeling for Speech Processing / Najlacnejšie knihy
Advances in Non-Linear Modeling for Speech Processing

Code: 01426988

Advances in Non-Linear Modeling for Speech Processing

by Raghunath S. Holambe, Mangesh S. Deshpande

Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition. §Non-linear aeroacoustic modeling approach is us ... more

51.62

RRP: 55.89 €

You save 4.28 €


In stock at our supplier
Shipping in 5 - 8 days
Add to wishlist

You might also like

Give this book as a present today
  1. Order book and choose Gift Order.
  2. We will send you book gift voucher at once. You can give it out to anyone.
  3. Book will be send to donee, nothing more to care about.

Book gift voucher sampleRead more

More about Advances in Non-Linear Modeling for Speech Processing

You get 125 loyalty points

Book synopsis

Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition. §Non-linear aeroacoustic modeling approach is used to estimate the important fine-structure speech events, which are not revealed by the short time Fourier transform (STFT). This aeroacostic modeling approach provides the impetus for the high resolution Teager energy operator (TEO). This operator is characterized by a time resolution that can track rapid signal energy changes within a glottal cycle. §The cepstral features like linear prediction cepstral coefficients (LPCC) and mel frequency cepstral coefficients (MFCC) are computed from the magnitude spectrum of the speech frame and the phase spectra is neglected. To overcome the problem of neglecting the phase spectra, the speech production system can be represented as an amplitude modulation-frequency modulation (AM-FM) model. To demodulate the speech signal, to estimation the amplitude envelope and instantaneous frequency components, the energy separation algorithm (ESA) and the Hilbert transform demodulation (HTD) algorithm are discussed. §Different features derived using above non-linear modeling techniques are used to develop a speaker identification system. Finally, it is shown that, the fusion of speech production and speech perception mechanisms can lead to a robust feature set.

Book details

Book category Books in English Technology, engineering, agriculture Other technologies & applied sciences Applied optics

51.62

Trending among others



Collection points Bratislava a 12770 dalších

Copyright ©2008-26 najlacnejsie-knihy.sk All rights reservedPrivacyCookies


Account: Log in
Všetky knihy sveta na jednom mieste. Navyše za skvelé ceny.

Shopping cart ( Empty )

For free shipping
shop for 59,99 € and more

You are here: